منابع مشابه
Different Objective Functions in Fuzzy c-Means Algorithms and Kernel-Based Clustering
An overview of fuzzy c-means clustering algorithms is given where we focus on different objective functions: they use regularized dissimilarity, entropy-based function, and function for possibilistic clustering. Classification functions for the objective functions and their properties are studied. Fuzzy c-means algorithms using kernel functions is also discussed with kernelized cluster validity...
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Hierarchical clustering is a recursive partitioning of a dataset into clusters at an increasingly finer granularity. Motivated by the fact that most work on hierarchical clustering was based on providing algorithms, rather than optimizing a specific objective, [19] framed similarity-based hierarchical clustering as a combinatorial optimization problem, where a ‘good’ hierarchical clustering is ...
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– We use a Gaussian radial basis kernel function to map pairs of feature vectors from a sample into a fuzzy connectivity matrix whose entries are fuzzy truths that the vector pairs belong to the same classes. To reduce the matrix size when the data set is large, we obtain a smaller set of representative vectors to form a smaller matrix. To this end we first group the feature vectors into many s...
متن کاملLocal Self-concordance of Barrier Functions Based on Kernel-functions
Many efficient interior-point methods (IPMs) are based on the use of a self-concordant barrier function for the domain of the problem that has to be solved. Recently, a wide class of new barrier functions has been introduced in which the functions are not self-concordant, but despite this fact give rise to efficient IPMs. Here, we introduce the notion of locally self-concordant barrier functio...
متن کاملClustering via Similarity Functions: Theoretical Foundations and Algorithms∗
Problems of clustering data from pairwise similarity information arise in many different fields. Yet the question of which algorithm is best to use under what conditions, and how good a notion of similarity does one need in order to cluster accurately remains poorly understood. In this work we propose a new general framework for analyzing clustering from similarity information that directly add...
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ژورنال
عنوان ژورنال: Journal of Japan Society for Fuzzy Theory and Intelligent Informatics
سال: 2009
ISSN: 1347-7986,1881-7203
DOI: 10.3156/jsoft.21.4_429